Recognition of forest species and ages using algorithms based on error-correcting output codes
Автор: Dmitriev Egor V., Kozoderov Vladimir V., Dementyev Alexander O., Sokolov Anton A.
Журнал: Журнал Сибирского федерального университета. Серия: Техника и технологии @technologies-sfu
Статья в выпуске: 6 т.10, 2017 года.
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The basic model of the recognition of forest inventory characteristics using spectral features is represented in the framework of the problem of hyperspectral airborne imagery processing. The algorithm of multiclass supervised classification based on the error-correcting output codes underlies this model. The support vector machine method is used as the necessary binary classifier. The method of the construction of training set by using mixed forest plots is represented. Results of the retrieval of species and age composition of forest stands from hyperspectral images are represented for the selected test area. The estimate of accuracy of the retrieval of the mixed forest composition is comparable with the accuracy of ground-based forest inventory data.
Remote sensing, pattern recognition, spectral classification, hyperspectral measurements
Короткий адрес: https://sciup.org/146115247
IDR: 146115247 | DOI: 10.17516/1999494X-2017-10-6-794-804
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